{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-kernel-two-sample-test-for-brain-networks","title":"The Kernel Two-Sample Test for Brain Networks","arxiv_id":"1511.06120","date":"2015-11-19","proceeding":null,"authors":["Emanuele Olivetti","Sandro Vega-Pons","Paolo Avesani"],"abstract":"In clinical and neuroscientific studies, systematic differences between two\npopulations of brain networks are investigated in order to characterize mental\ndiseases or processes. Those networks are usually represented as graphs built\nfrom neuroimaging data and studied by means of graph analysis methods. The\ntypical machine learning approach to study these brain graphs creates a\nclassifier and tests its ability to discriminate the two populations. In\ncontrast to this approach, in this work we propose to directly test whether two\npopulations of graphs are different or not, by using the kernel two-sample test\n(KTST), without creating the intermediate classifier. We claim that, in\ngeneral, the two approaches provides similar results and that the KTST requires\nmuch less computation. Additionally, in the regime of low sample size, we claim\nthat the KTST has lower frequency of Type II error than the classification\napproach. Besides providing algorithmic considerations to support these claims,\nwe show strong evidence through experiments and one simulation.","url_abs":"http://arxiv.org/abs/1511.06120v1","url_pdf":"http://arxiv.org/pdf/1511.06120v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"the-kernel-two-sample-test-for-brain-networks","repo_url":"https://github.com/emanuele/jstsp2015","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"two","task_name":"Vocal Bursts Valence Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}